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Fully dynamic maintenance of euclidean minimum spanning trees
We maintain the minimum spanning tree of a point set in the plane, subject to point insertions and deletions, in time O(n^5/6 log1^2/2 n) per update operation. No nontrivial dynamic geometric minimum spanning tree algorithm was previously known. We reduce the problem to maintaining bichromatic closest pairs, which we also solve in the same time bounds. Our algorithm uses a novel construction, the ordered nearest neighbors of a sequence of points. Any point set or bichromatic point set can be ordered so that this graph is a simple path
Planar PØP: feature-less pose estimation with applications in UAV localization
© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.We present a featureless pose estimation method that, in contrast to current Perspective-n-Point (PnP) approaches, it does not require n point correspondences to obtain the camera pose, allowing for pose estimation from natural shapes that do not necessarily have distinguished features like corners or intersecting edges. Instead of using n correspondences (e.g. extracted with a feature detector) we will use the raw polygonal representation of the observed shape and directly estimate the pose in the pose-space of the camera. This method compared with a general PnP method, does not require n point correspondences neither a priori knowledge of the object model (except the scale), which is registered with a picture taken from a known robot pose. Moreover, we achieve higher precision because all the information of the shape contour is used to minimize the area between the projected and the observed shape contours. To emphasize the non-use of n point correspondences between the projected template and observed contour shape, we call the method Planar PØP. The method is shown both in simulation and in a real application consisting on a UAV localization where comparisons with a precise ground-truth are provided.Peer ReviewedPostprint (author's final draft
Joint Compressed Sensing and Manipulation of Wireless Emissions with Intelligent Surfaces
Programmable, intelligent surfaces can manipulate electromagnetic waves
impinging upon them, producing arbitrarily shaped reflection, refraction and
diffraction, to the benefit of wireless users. Moreover, in their recent form
of HyperSurfaces, they have acquired inter-networking capabilities, enabling
the Internet of Material Properties with immense potential in wireless
communications. However, as with any system with inputs and outputs, accurate
sensing of the impinging wave attributes is imperative for programming
HyperSurfaces to obtain a required response. Related solutions include field
nano-sensors embedded within HyperSurfaces to perform minute measurements over
the area of the HyperSurface, as well as external sensing systems. The present
work proposes a sensing system that can operate without such additional
hardware. The novel scheme programs the HyperSurface to perform compressed
sensing of the impinging wave via simple one-antenna power measurements. The
HyperSurface can jointly be programmed for both wave sensing and wave
manipulation duties at the same time. Evaluation via simulations validates the
concept and highlight its promising potential.Comment: Published at IEEE DCOSS 2019 / IoT4.0 workshop
(https://www.dcoss.org/workshops.html). Funded by the European Union via the
Horizon 2020: Future Emerging Topics - Research and Innovation Action call
(FETOPEN-RIA), grant EU736876, project VISORSURF (http://www.visorsurf.eu
Maghemite-like regions at crossing of two antiphase boundaries in doped BiFeO3
We report the observation of a novel structure at the point where two antiphase boundaries cross in a doped bismuth ferrite of composition (Bi0.85Nd0.15)(Fe0.9Ti0.1)O0.3. The structure was investigated using a combination of high angle annular dark field imaging and electron energy loss spectroscopy spectrum imaging in the scanning transmission electron microscope. A three-dimensional model was constructed by combining the position and chemistry data with previous results and assuming octahedral coordination of all Fe and Ti atoms. The resulting structure shows some novel L shaped arrangements of iron columns, which are coordinated in a similar manner to FeO6 octahedra in maghemite. It is suggested that this may lead to local ferromagnetic orderings similar to those in maghemite
A Convex Polynomial Force-Motion Model for Planar Sliding: Identification and Application
We propose a polynomial force-motion model for planar sliding. The set of
generalized friction loads is the 1-sublevel set of a polynomial whose gradient
directions correspond to generalized velocities. Additionally, the polynomial
is confined to be convex even-degree homogeneous in order to obey the maximum
work inequality, symmetry, shape invariance in scale, and fast invertibility.
We present a simple and statistically-efficient model identification procedure
using a sum-of-squares convex relaxation. Simulation and robotic experiments
validate the accuracy and efficiency of our approach. We also show practical
applications of our model including stable pushing of objects and free sliding
dynamic simulations.Comment: 2016 IEEE International Conference on Robotics and Automation (ICRA
Point cloud segmentation using hierarchical tree for architectural models
Recent developments in the 3D scanning technologies have made the generation
of highly accurate 3D point clouds relatively easy but the segmentation of
these point clouds remains a challenging area. A number of techniques have set
precedent of either planar or primitive based segmentation in literature. In
this work, we present a novel and an effective primitive based point cloud
segmentation algorithm. The primary focus, i.e. the main technical contribution
of our method is a hierarchical tree which iteratively divides the point cloud
into segments. This tree uses an exclusive energy function and a 3D
convolutional neural network, HollowNets to classify the segments. We test the
efficacy of our proposed approach using both real and synthetic data obtaining
an accuracy greater than 90% for domes and minarets.Comment: 9 pages. 10 figures. Submitted in EuroGraphics 201
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